Enterprises today have greater flexibility in determining whether investing in applications, platforms and infrastructure should be a capital expenditure or operational expenditure or both. As such enterprises are increasingly using a mix of public cloud, private cloud and on-premises strategy to gain sustainable competitive advantage. However, enterprises have to ensure that business processes run effectively and reliably irrespective of whether the applications and its associated data are on the on-premises instances or in the cloud.
For example, an enterprise which has adopted a CRM strategy could be relying on an on-premises based marketing application used for developing and nurturing leads and could be using a SaaS based Sales application to create opportunities and quotes. The sales and the marketing teams which use these systems need to be able to access and share the data in a reliable and cohesive way. This example can be extended to other applications areas such as HR, Supply Chain, and Finance and the demands the users place on getting a consistent view of the data.
Another example, an enterprise may have established on-premises based Business Intelligence and Reporting platform which is used by employees in various roles to retrieve their respective reports and perform analysis. Typically, a Business Intelligence platform requires data from various sources to be aggregated so it can provide rich capabilities to slice and dice the data. Enterprises which have a mix of public cloud, private cloud and on-premises will need to ensure that the relevant data from these sources are made available to the Business Intelligence system.
Most enterprises have spent years avoiding the data “silos” that inhibit productivity. IT has had its fill of new integration paradigms, from CORBA to Client/Server to Web services, EAI, SOA and replicating databases. After decades of locking down critical issues such as interface definitions, governance, reliability, transaction management, exception handling, and transaction monitoring, it is imperative to extend these solutions into environments which has a mix of cloud and on-premises applications and its associated data.
Refer to my blog and an associated technical white paper on this subject – https://blogs.oracle.com/dataintegration/entry/replicating_between_cloud_and_on
Share your comments on how your organization data is distributed between the cloud and on-premises and what solutions are you adopting to keep it consistent in real-time ?